Sunday, 20 September 2020 15:38
The Department of Computer Science awarded a master’s degree to Hassan Khalil Salman in Computer Science / General for his thesis tagged "Web of Things Using Quick Respone Code."
"Breast Cancer Staging System Using Rapid Response Code"
Wednesday 08/12/2020 In the discussion room in the building of the Computer Science Department, the discussion committee consisted of:
Prof. Dr. Abbas Fadel Muhammad Ali as Chairman
Prof. Israa Tahseen Ali, member
Dr. Shatha Habib Jaafar, Member
Prof. Dr. Iqbas Ezzeddine as a member and supervisor
The thesis dealt with the role that computers play in detecting early signs of cancer compared to the human vision system. In this thesis, classification techniques are based on machine learning, which is used to classify a data set of breast cancers.
The proposed system uses three classification algorithms. The first classifier is KNN, the second classifier is NB, and the third classifier is J48.
The method obtained 95.8.5% accuracy and the QR code was used safely.
"Breast Cancer Staging System Using Rapid Response Code"
Wednesday 08/12/2020 In the discussion room in the building of the Computer Science Department, the discussion committee consisted of:
Prof. Dr. Abbas Fadel Muhammad Ali as Chairman
Prof. Israa Tahseen Ali, member
Dr. Shatha Habib Jaafar, Member
Prof. Dr. Iqbas Ezzeddine as a member and supervisor
The thesis dealt with the role that computers play in detecting early signs of cancer compared to the human vision system. In this thesis, classification techniques are based on machine learning, which is used to classify a data set of breast cancers.
The proposed system uses three classification algorithms. The first classifier is KNN, the second classifier is NB, and the third classifier is J48.
The method obtained 95.8.5% accuracy and the QR code was used safely.
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Master theses
